Production hardening: security fixes, code quality, 724 skills complete

- Fix 25 shell=True subprocess calls with list-based commands
- Fix 49 verify=False in defensive skills (env-var override)
- Add timeout to 231 HTTP/subprocess/socket calls
- Fix 6 SQL injection patterns with whitelist validation
- Replace 8 __import__() with standard imports
- Remove 701 unused imports across 442 files
- Add authorized-testing disclaimers to all offensive skills
- Complete 11 incomplete skill directories
- Expand 10 stub SKILL.md files with full content
- Fix 2 YAML parse errors in frontmatter
- Fix 5 pre-existing syntax errors
- Convert 22 hardcoded paths/ports to environment variables
- Back up 21 redundant skill pairs to .bak
- Fix 2 global declaration errors
- 724/724 skills with full folder anatomy (SKILL.md + agent.py + api-reference.md + LICENSE)
- 0 compile errors across all 724 agent.py files

skills/detecting-business-email-compromise-with-ai/SKILL.md

@@ -20,7 +20,7 @@ AI-powered BEC detection uses machine learning, NLP, and behavioral analytics to
 - SIEM for alert correlation and investigation
 - Understanding of BEC attack types (FBI IC3 classification)
 
-## Implementation Steps
+## Workflow
 
 ### Step 1: Deploy AI Email Security Platform
 - Select API-based solution (Abnormal Security, Tessian, Ironscales) or enhance existing SEG

skills/detecting-business-email-compromise-with-ai/scripts/agent.py

@@ -9,7 +9,6 @@ import argparse
 import json
 import math
 import re
-import sys
 from collections import Counter
 
 URGENCY_WORDS = {"urgent", "immediately", "asap", "deadline", "critical",